Author

Yanran Ma

Shanghai Jiao Tong University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Organism:human· 2 Approach:deep learning· 1 Assay:imaging· 1 Research Focus:protein structure prediction· 1 Research Focus:spatial domain detection· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Ruitian GaoiD· 2 shared Ting WeiiD· 2 shared Zhangsheng YuiD· 2 shared Botao FaiD· 1 shared Guoqiang CheniD· 1 shared Jing SuniD· 1 shared Junke ZhengiD· 1 shared Luke J. JohnstoniD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioinformatics

Ruitian GaoORCID

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2 papers

Recent·Most cited

HEARTSVG: a fast and accurate method for spatially variable gene identification in large-scale spatial transcriptomic data

Xin Yuan, Yanran Ma, Ruitian Gao, Shuya Cui, Yifan Wang, Botao Fa, Shiyang Ma, Ting Wei, Shuangge Ma, Zhangsheng Yu

HEARTSVG identifies spatially variable genes in spatial transcriptomic data with high accuracy and efficiency, uncovering biologically significant patterns in colorectal cancer.

Nature Communications · Jul 7, 2024Peer-reviewedBioinformatics

Predicting Gene Spatial Expression and Cancer Prognosis: An Integrated Graph and Image Deep Learning Approach Based on HE Slides

Ruitian Gao, Xin Yuan, Yanran Ma, Ting Wei, Luke J. Johnston, Yanfei Shao, Wenwen Lv, Tengteng Zhu, Yue Zhang, Junke Zheng, Guoqiang Chen, Jing Sun, Yu Guang Wang, Zhangsheng Yu

The paper introduces an IGI-DL model that predicts gene spatial expression from HE images and improves cancer prognosis using a risk score derived from predicted gene expression.

Cell Reports Medicine · May 1, 2024Peer-reviewedBioinformatics